A Wavelet-Based Denoising System Using Time-Frequency Adaptation for Speech Enhancement

In this paper, we propose a novel wavelet denoising system using time-frequency adaptation for providing speech enhancement robustness to non-stationary and colored noise. Different from the conventional methods in threshold choosing, e.g. invariant threshold and time-variant threshold, the proposed wavelet coefficient threshold (WCT) is adapted by both time and frequency information. In order to further improve the intelligibility of the processed speech signal, we apply appropriate wavelet thresholding according to voiced/unvoiced decision. Simulation results showed that the proposed system is capable of reducing noise with little speech degradation and the overall performance is superior to several competitive methods in both objective and subjective evaluations.